Coastline detection method of remote sensing image based on local information fuzzy clustering

Tinglu Cai; Jun Sheng; Zhenchao Qu

doi:10.1117/12.3019595

23 January 2024 Coastline detection method of remote sensing image based on local information fuzzy clustering

Tinglu Cai, Jun Sheng, Zhenchao Qu

Proceedings Volume 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023); 129782V (2024) https://doi.org/10.1117/12.3019595
Event: 2023 4th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2023), 2023, wuhan, China

Abstract

The traditional coastline detection method is affected by the surrounding environment, leading to some error of the acoustic wave, which affects the detection effect of the coastline. Therefore, a method for remote sensing image coastline detection based on local information fuzzy clustering is designed. The differential edge features of coastline remote sensing images were extracted, and the superpixels of remote sensing images were segmented and clustered for the whole remote sensing image pixels. The coastline detection model of the remote sensing image is established to realize the accurate detection of the coastline in the remote sensing image. Simulation experiments verify that the proposed detection method has high detection accuracy and can be applied to practical applications.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tinglu Cai, Jun Sheng, and Zhenchao Qu "Coastline detection method of remote sensing image based on local information fuzzy clustering", Proc. SPIE 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023), 129782V (23 January 2024); https://doi.org/10.1117/12.3019595

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